Spatiotemporal patterns and determinants of agricultural resilience in the Yellow River Basin
Year: 2025
Type: article
Abstract: Introduction This study investigates the spatiotemporal evolution and determinants of agricultural resilience across 43 prefecture-level cities in the Yellow River Basin from 2012 to 2022. It aims to provide insights into spatial patterns, regional disparities, and the key factors influencing resilience to support sustainable agricultural development. Methods The entropy method was used to assign weights to selected indicators of agricultural resilience. Spatial analysis techniques, including Moran’s Index, the Gini coefficient, and Kernel density estimation, were applied to examine spatial patterns and temporal trends. The obstacle degree model and the spatial Durbin model were employed to identify internal and external drivers affecting agricultural resilience. Results Findings reveal a steady upward trend in agricultural resilience with notable spatial agglomeration and spillover effects. Although overall disparities have narrowed, significant differences persist between upstream and other regions. Internal constraints include low agricultural insurance coverage, limited effective irrigation, and reduced land productivity. External factors such as urbanization, economic development, and skilled agricultural labor enhance resilience, while industrialization negatively affects it. Discussion The study highlights the need for targeted regional interventions, improved spatial coordination, and optimized cross-regional resource allocation to strengthen agricultural resilience and promote sustainable development in the Yellow River Basin.
Authors: Chengyao Ma, Shilei Wu, Xiaoqian Huo
Institution: Shandong University of Technology
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W4412765607